Podcasts links:
Youtube : youtu.be/SbFp4fnuxjo
Spotify : open.spotify.com/episode/6s13...

#medical-ai #healthcare #research #llms

🔬 Special Focus: Medical Ethics & AI
- Clinical Trust Impact Study
- Mental Health AI Challenges
- Hospital Monitoring Ethics
- Radiology AI Integration

💻 LLM Applications
- Patient-Friendly Video Reports
- Medical Video QA Systems
- Gene Ontology Annotation
- Healthcare Recommendations

📊 Benchmarks & Evaluations
> Multi-OphthaLingua
- Multilingual ophthalmology benchmark
- Focus on LMICs healthcare
- Bias assessment framework
- ACE-M3 Evaluation Framework
- Multimodal medical model testing
- Comprehensive capability assessment
- Standardized evaluation metrics

🔧 Frameworks & Methods
- ReflecTool: Reflection-Aware Clinical Agents
- Process-Supervised Clinical Notes
- Federated Learning with RAG
- Query Pipeline Optimization

🤖 Medical LLM & Other Models
- MedMax: Mixed-Modal Biomedical Assistant
- Advanced multimodal instruction tuning
- Enhanced biomedical knowledge integration
- Comprehensive assistant capabilities

5/5 For daily insights into Medical AI breakthroughs:

💬 Discord: discord.gg/A5Fjf5zC69
📺 YouTube: youtube.com/@OpenlifesciAI
🎧 Spotify: open.spotify.com/show/4edRuST...

4/5 Key Models in HAI-DEF

• CXR Foundation: Models like ELIXR-C & ELIXR-B excel in chest radiography tasks.

• Path Foundation: ViT-based models for stain-agnostic histopathology image analysis.

• Derm Foundation: BiT ResNet models for diverse dermatology tasks.

3/5 Why HAI-DEF Matters

Building robust medical AI is costly and data-intensive. HAI-DEF:

- Speeds up development with pre-trained models.
- Overcomes data scarcity for rare conditions.
- Reduces computing needs.

2/5 HAI-DEF provides:

- Pre-trained foundation models for X-rays, CT, histopathology, dermatology, & audio.

- Compact embeddings requiring less labeled data, reducing training times and costs.

- Open-source tools and research endpoints for easy integration.

It's encouraging to see tech companies like Google, Microsoft, and OpenAI, have already adopted our benchmarks to evaluate their models. 🔥